Principle of Proportional Ink

library(tidyverse)

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library(ggformula)

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## New to ggformula?  Try the tutorials: 
##  learnr::run_tutorial("introduction", package = "ggformula")
##  learnr::run_tutorial("refining", package = "ggformula")

library(nycflights13)

theme_set(theme_bw(base_size = 18))

head(flights)

## # A tibble: 6 × 19
##    year month   day dep_time sched_dep_time dep_delay arr_time sched_arr_time
##   <int> <int> <int>    <int>          <int>     <dbl>    <int>          <int>
## 1  2013     1     1      517            515         2      830            819
## 2  2013     1     1      533            529         4      850            830
## 3  2013     1     1      542            540         2      923            850
## 4  2013     1     1      544            545        -1     1004           1022
## 5  2013     1     1      554            600        -6      812            837
## 6  2013     1     1      554            558        -4      740            728
## # … with 11 more variables: arr_delay <dbl>, carrier <chr>, flight <int>,
## #   tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>,
## #   hour <dbl>, minute <dbl>, time_hour <dttm>

avg_dist <- flights %>%
  group_by(carrier) %>%
  summarise(avg_dist = mean(distance, na.rm = TRUE),
            sd_dist = sd(distance, na.rm = TRUE)) %>%
  left_join(airlines) %>%
  filter(avg_dist > 1000 & avg_dist < 4000)

## Joining, by = "carrier"

avg_dist

## # A tibble: 7 × 4
##   carrier avg_dist sd_dist name                  
##   <chr>      <dbl>   <dbl> <chr>                 
## 1 AA         1340.   638.  American Airlines Inc.
## 2 AS         2402      0   Alaska Airlines Inc.  
## 3 B6         1069.   704.  JetBlue Airways       
## 4 DL         1237.   660.  Delta Air Lines Inc.  
## 5 F9         1620      0   Frontier Airlines Inc.
## 6 UA         1529.   799.  United Air Lines Inc. 
## 7 VX         2499.    88.0 Virgin America

ggplot(avg_dist, aes(x = avg_dist, y = name)) +
  geom_col() +
  xlab("Average Distance Flown") + 
  ylab("Airline Name") + 
  coord_cartesian(xlim = c(1000, 2500))

Pitfalls of color use

avg_dist <- flights %>%
  group_by(carrier) %>%
  summarise(avg_dist = mean(distance, na.rm = TRUE),
            sd_dist = sd(distance, na.rm = TRUE),
            avg_delay = mean(arr_delay, na.rm = TRUE)) %>%
  left_join(airlines) 

## Joining, by = "carrier"

avg_dist

## # A tibble: 16 × 5
##    carrier avg_dist sd_dist avg_delay name                       
##    <chr>      <dbl>   <dbl>     <dbl> <chr>                      
##  1 9E          530.   322.      7.38  Endeavor Air Inc.          
##  2 AA         1340.   638.      0.364 American Airlines Inc.     
##  3 AS         2402      0      -9.93  Alaska Airlines Inc.       
##  4 B6         1069.   704.      9.46  JetBlue Airways            
##  5 DL         1237.   660.      1.64  Delta Air Lines Inc.       
##  6 EV          563.   287.     15.8   ExpressJet Airlines Inc.   
##  7 F9         1620      0      21.9   Frontier Airlines Inc.     
##  8 FL          665.   161.     20.1   AirTran Airways Corporation
##  9 HA         4983      0      -6.92  Hawaiian Airlines Inc.     
## 10 MQ          570.   226.     10.8   Envoy Air                  
## 11 OO          501.   206.     11.9   SkyWest Airlines Inc.      
## 12 UA         1529.   799.      3.56  United Air Lines Inc.      
## 13 US          553.   584.      2.13  US Airways Inc.            
## 14 VX         2499.    88.0     1.76  Virgin America             
## 15 WN          996.   410.      9.65  Southwest Airlines Co.     
## 16 YV          375.   160.     15.6   Mesa Airlines Inc.

ggplot(avg_dist, aes(x = avg_dist, y = avg_delay)) + 
  geom_point(aes(color = name), size = 4) + 
  xlab("Average Distance Flown") + 
  ylab("Average Arrival Delay")

ggplot(flights, aes(x = distance, y = arr_delay, color = carrier)) + 
  geom_point(size = 4) + 
  xlab("Distance Flown") +
  ylab("Arrival Delay")

## Warning: Removed 9430 rows containing missing values (geom_point).

Visualize Uncertainty

ggplot(avg_dist, aes(x = avg_dist, y = name)) + 
  geom_col() + 
  xlab("Average Distance Flown") + 
  ylab("")